1. Technical Field
This invention is directed toward a system and method for encoding and decoding color image data. More particularly, this invention is directed toward a system and method for compressing image data formatted in a mosaiced sampling pattern by employing a reversible color transform.
2. Background Art
Typical digital cameras use a single light sensitive sensor and a color filter array. Each pixel element in the color filter array records the intensity information of a single color component, typically red, green or blue. In most applications, the captured data is interpolated into a full color image, which is then compressed. A Bayer-patterned color filter array is often used as the preferred color filter array. In this type of filter, green filters are interlaced with red and blue filters.
It has been noted, however, that when color interpolation is performed before compression, instead of after compression, better image quality and higher compression ratios can be achieved. Typically the goal in image compression is to increase the compression ratio of the compressed data while maintaining high image quality.
There are various problems with known image compression systems, however, even those that interpolate before compressing the data. For instance, direct compression of color filter array data with Joint Photographic Experts Group (JPEG) compression produces poor quality images. If, however, the Bayer patterned color filter array data is separated into the three primary components (red, green, blue), the red and blue components can be down-sampled into a compact rectangular array and compressed directly. To do this it is necessary to find a transformation of the quincunx green pixels typical of the Bayer format into a form suitable for compression. Lee and Ortega [3] use a reversible transformation that maps pixel information from the Bayer pattern color filter array into another range. The mapping rotates the original interlaced array into a rhombus, packing the data together. However, the shape of the data to be compressed after transformation is not rectangular and thus is not suitable for typical JPEG compression. Toi and Ohita [2] apply sub-band decomposition to compress the color filter array data using a non-separable two-dimensional diamond filter to process the quincunx green array. The sub-bands are then encoded for optimum rate-distortion. Reconstruction of the image data is carried out by decoding, synthesizing and interpolating the data to obtain the resultant full color image. This method is also somewhat computationally expensive and since it does not allow for exact invertibility in integer arithmetic it is not suitable for lossless compression. Koh, Mukherjee and Mitra [4] also devised a method of compressing color filter array data before full color interpolation. In this system, image content affected the performance of the compression and interpolation algorithms and sometimes adversely affected the image quality.
In general, there are two types of compression—lossy and lossless. Lossless compression allows exact original data to be recovered after compression and decompression, while lossy compression allows for the data to be recovered after compression and decompression to vary slightly from the original data. There is a tradeoff between these two types of compression in that lossy compression typically provides for a better compression ratio than lossless compression, while lossless compression provides a better image quality after decompression.
It is noted that in the remainder of this specification, the description refers to various individual publications identified by a numeric designator contained within a pair of brackets. For example, such a reference may be identified by reciting, “reference [1]” or simply “[1]”. A listing of the publications corresponding to each designator can be found at the end of the Detailed Description section.